two_valuable

本代码实现了基于肤色的人脸分割程序，代码采用Matlab编写，包含了四个测试样例和结果分析。(This is matlab code about face detection based on face color.)

说明：  利用BOW结合空间金字塔模型，使用支持向量机进行图像分类(Image classification using bow)

说明：  数字图像处理(Digital Image Processing)是通过计算机对图像进行去除噪声、增强、复原、分割、提取特征等处理的方法和技术。 [1] 数字图像处理的产生和迅速发展主要受三个因素的影响：一是计算机的发展；二是数学的发展（特别是离散数学理论的创立和完善）;三是广泛的农牧业、林业、环境、军事、工业和医学等方面的应用需求的增长(Digital Image Processing (DIP) is a method and technology of removing noise, enhancing, restoring, segmenting and extracting features from images by computer. [1] The emergence and rapid development of digital image processing are mainly influenced by three factors: first, the development of computer; second, the development of mathematics (especially the establishment and improvement of discrete mathematics theory); third, the growth of the demand for extensive applications in agriculture, animal husbandry, forestry, environment, military, industry and medicine.)

粒子滤波算法实现目标定位的程序，matlab(Particle filter algorithm targeting program)

sift算法引用于图像处理的一些常用程序(a reference to the image processing algorithms sift some common procedures)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

该文件包含与以下文件相关的代码： Y.Liu和Z.Wang具有自适应稀疏表示的同时图像融合和去噪(This package contains the code which is associated with the following paper: Y. Liu and Z. Wang Simultaneous image fusion and denoising with adaptive sparse representatio)

新一代的arnold图像之乱变换算法，文件中详细说明了代码的含义，达到一定迭代次数后图像可以复原，是学习图像加密同学的必备代码(The chaos of a new generation of arnold image transformation algorithm, the paper detailed the meaning of the code, after a certain number of iterations the image can be restored, is essential for students to learn the code image encryption)

这个实例就像一个魔镜一样，能把原始图像照出各种变换效果,是基于MFC的多文档应用程序(This example is like a mirror,which can convert original image according to a variety of effects)

一个很好类子来说明类模板的使用，可以比较明了类模板的使用方法，最好进行单步调试(use of class template )